Jingchen Liu
Impact in
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- Psychometric Methodologies and Testing
- Probability and Risk Models
- Statistics and Probability top 1%
- Statistical Methods and Inference
- Statistical Methods and Bayesian Inference
Papers in
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- Probability and Risk Models 29
- Psychometric Methodologies and Testing 11
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- Statistical Methods and Inference 10
- Co-authors
- Zhiliang YingGongjun XuAndrew GelmanYeojin ChungVincent DorieSophia Rabe‐HeskethXiaoou LiJosé Blanchet
- Journals
- Psychometrika (10 papers)Advances in Applied Probability (8 papers)Applied Psychological Measurement (5 papers)Journal of Applied Probability (4 papers)British Journal of Mathematical and Statistical Psychology (3 papers)
- Partner nations
- United StatesChinaUnited Kingdom
In The Last Decade
Jingchen Liu
91 papers receiving 2.1k citations
Hit Papers
Peers
Comparison fields: 5 of 168
- Management Science and Operations Research 551
- Statistics and Probability 351
- Computer Science Applications 156
- Artificial Intelligence 586
- Statistics, Probability and Uncertainty 102
Countries citing papers authored by Jingchen Liu
This map shows the geographic impact of Jingchen Liu's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jingchen Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jingchen Liu more than expected).
Fields of papers citing papers by Jingchen Liu
This network shows the impact of papers produced by Jingchen Liu. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jingchen Liu. The network helps show where Jingchen Liu may publish in the future.
Co-authors
The 25 scholars most cited alongside Jingchen Liu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2024 | 1 | |
| 3 | 2022 | 10 | |
| 4 | 2019 | 36 | |
| 5 | 2018 | 10 | |
| 6 | 2018 | 9 | |
| 7 | 2018 | 7 | |
| 8 | 2015 | 6 | |
| 9 | Statistical analysis of Q-matrix based diagnostic classification models | 2015 | 22 |
| 10 | 2014 | 127 | |
| 11 | 2013 | 9 | |
| 12 | 2012 | 1 | |
| 13 | 2012 | 0 | |
| 14 | 2011 | 2 | |
| 15 | 2010 | 14 | |
| 16 | Recognizing Biomedical Named Entities Using Skip-Chain Conditional Random Fields | 2010 | 13 |
| 17 | 2008 | 3 | |
| 18 | 2008 | 14 | |
| 19 | 2007 | 1 | |
| 20 | 2006 | 4 |
About Jingchen Liu
Jingchen Liu is a scholar working on Management Science and Operations Research, Statistics and Probability, Finance, Statistics, Probability and Uncertainty and Demography, having authored 97 papers that have together received 2.1k indexed citations. Recurring topics across this work include Probability and Risk Models (29 papers), Financial Risk and Volatility Modeling (16 papers), Insurance, Mortality, Demography, Risk Management (11 papers), Psychometric Methodologies and Testing (11 papers), Statistical Methods and Inference (10 papers), Stochastic processes and financial applications (7 papers), Bayesian Methods and Mixture Models (7 papers) and Advanced Statistical Process Monitoring (6 papers). The work is most often cited by research in Management Science and Operations Research (551 citations), Statistics and Probability (351 citations), Computer Science Applications (156 citations), Artificial Intelligence (586 citations) and Statistics, Probability and Uncertainty (102 citations). Jingchen Liu has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Zhiliang Ying, Gongjun Xu, Andrew Gelman, Yeojin Chung, Vincent Dorie, Sophia Rabe‐Hesketh, Xiaoou Li, José Blanchet, Yunxiao Chen and Yanxi Liu. Their work appears in journals such as Psychometrika, Advances in Applied Probability, Applied Psychological Measurement, Journal of Applied Probability and British Journal of Mathematical and Statistical Psychology.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.